Lessons Learned and Future Work
8
Challenges and Solutions
- Data Constraints: Limited data depth made it difficult to derive detailed insights. Nevertheless, I maximized the available information to provide useful, albeit broader, conclusions.
- Insight Generation: Despite the data challenges, I employed creative strategies to extract meaningful insights, emphasizing the need for more detailed data in future work.

Future Considerations
- Real-Time Data Integration: Implementing real-time data could allow for quicker responses to issues as they arise.
- Model Expansion: Broadening the model to include more patient demographics and conditions would increase its applicability.
- Advanced Techniques: Utilizing deep learning could enhance prediction accuracy.
- Automated Alerts: Developing automated alerts based on predictions could improve proactive care and decision-making.
Healthcare Data Challenges and Their Impacts
Common Healthcare Data Management Issues and How to Solve Them
Health Data Management: Challenges and Best Practices